Policymakers and donors often need to identify the locations and settings where technologies are most likely to have important effects, to increase the benefits from agricultural development or extension efforts. Higher quality information may help to target the high-payoff locations. The value of information (VOI) in this context is formalized by evaluating the results of decision making guided by a set of information compared to the results of acting without taking the information into account. We present a framework for management performance mapping that includes evaluating the VOI for decision making about geographic priorities in regional intervention strategies, in case studies of Andean and Kenyan potato seed systems. We illustrate use of Bayesian network models and recursive partitioning to characterize the relationship between seed health and yield responses and environmental and management predictors used in studies of seed degeneration. These analyses address the expected performance of an intervention based on geographic predictor variables. In the Andean example, positive selection of seed from asymptomatic plants was more effective at high altitudes in Ecuador. In the Kenyan example, there was the potential to target locations with higher technology adoption rates and with higher potato cropland connectivity, i.e., a likely more important role in regional epidemics. Targeting training to high performance areas would often provide more benefits than would random selection of target areas. We illustrate how assessing the VOI can help inform targeted development programs and support a culture of continuous improvement for interventions.

中文翻译：

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管理绩效图和信息价值对管理干预措施的区域优先排序

决策者和捐助者通常需要确定技术最有可能产生重要影响的地点和环境，以增加农业发展或推广工作的收益。较高质量的信息可能有助于确定高收益位置。在这种情况下，信息价值（VOI）通过评估一组信息指导下的决策结果与不考虑信息的行动结果来形式化。在安第斯和肯尼亚马铃薯种子系统的案例研究中，我们提供了一个管理绩效测绘框架，其中包括评估VOI，以便就区域干预策略中的地理优先事项做出决策。我们说明了使用贝叶斯网络模型和递归分区来表征种子健康与产量响应以及种子变性研究中使用的环境和管理预测指标之间的关系。这些分析基于地理预测变量来解决干预措施的预期效果。在安第斯山脉的例子中，在厄瓜多尔的高海拔地区，从无症状植物中积极选择种子更为有效。在肯尼亚的例子中，有可能以更高的技术采用率和更高的马铃薯耕地连通性为目标，这可能是在区域流行病中更重要的作用。与随机选择目标领域相比，将培训目标对准高性能领域通常会提供更多的好处。